Approaching the Past through Practice: Reconstruction of a Historical Greenlandic Dog Sled
Bibliographic record
Abstract
Abstract Since the emergence of the Thule culture (AD 1200), dog sledding has been perceived as a central means of transportation in traditional Inuit life in the Arctic. However, there is an absence of research concerning Inuit dog-sled technology and the tradition of the craft. This study investigates the Inuit dog-sled technocomplex using enskilment methodologiesby employing experimental and ethno-archaeological observations to explore the relationship between knowledge and technical practice. It involves the reconstruction of a historical West Greenlandic dog sled, shedding light on carpentry techniques and construction processes. This method emphasizes the interaction between humans, technology, and time, providing essential practical data for future archaeological and historical research, particularly for comprehending fragmented archaeological remains. By focusing on process rather than end product, this research provides insight into understanding Inuit dog sled technology and the complexity of the practice. The connection between artifacts and materially situated practice is demonstrated through the reconstruction of a dog sled, which illustrates the value of physicality in enskilment. It highlights how experimental archaeology can improve our insights into the historical and prehistoric Arctic societies’ technologies, economies, and practices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".